<BI Tool>
Business intelligence (BI) is a technique for a user attempting to freely analyze necessary data by himself/herself from huge quantities of data in a company accumulated from business systems and the like and utilize the analyzed data for decision-making in the company such as management plans and corporate strategies. A BI tool used for such purposes includes an intuitive human interface enabling a user to provide interactive instructions so that even a user who does not have intimate knowledge of systems and programming can use the tool, and allows retrieval and analysis using business terms that are usually used and flexible reporting of retrieval and analysis results in various formats.
<OLAP>
Data analysis with a BI tool is carried out using a technique of multi-dimensional analysis called online analytical processing (OLAP).
In the OLAP, data to be manipulated are handled as a cube having a multi-dimensional data structure defined as a set of multiple data aggregate items (dimensions) and quantitative value items (measures) (CODD: multi-dimensional concept view).
Data are also complete and consistent, which is a prerequisite (CODD: generality of dimension, inter-dimensional calculation process without constraints).
In the OLAP, analysis in a multi-dimensional aspect is, logically, conducted by extracting, typically, two-dimensional data from a multi-dimensional cube for analysis, displaying the extracted data in a form of a table, graph, chart, or the like, switching the display by analytical manipulation such as slicing, dicing, and drill-down/roll-up, and repeating these manipulations.
Slicing Taking out only specific members of multi-dimensional data at a section, and putting the taken members into a two-dimensional table.
Dicing Switching between vertical and horizontal items, and putting an entirely different section of the multi-dimensional data into a two-dimensional table.
Drill-down/roll-up Drill-down refers to manipulation of digging into an aggregate result to display more detailed breakdown data, and roll-up refers to a reverse of the manipulation.
<DWH, DM, ETL>
Typically, in an organization such as a company, multiple business systems are in operation where data are dispersed over various sources, and such data once need to be consolidated for data analysis.
An example of a technique for accumulating data collected from multiple business systems in time series, analyzing a large quantities of data, and making use of the analyzed data for decision making is a data warehouse (DWH). A data mart (DM) is usually smaller than a data warehouse, and collects data necessary for a specific theme or field and supports executives making strategic decisions on business. A retrieval result obtained through retrieval of data accumulated in a data warehouse, a data mart, or the like is reorganized and used as a multi-dimensional and multi-level cube for OLAP analysis.
For storing data occurring in business systems in databases and constructing a data warehouse or a data mart, ETL (extract, transform, and load) processes are required. ETL tools having functions necessary for a process of loading data into databases are often used recently, but this typically results in a complicated process since data are asynchronously supplied from a plurality of different information sources.